Nucleic Acids Research Advance Access originally published online on August 1, 2008
Nucleic Acids Research 2008 36(17):e110; doi:10.1093/nar/gkn485
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Nucleic Acids Research, 2008, Vol. 36, No. 17 e110
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Methods Online |
An approach of orthology detection from homologous sequences under minimum evolution
1Department of Agricultural Biotechnology, Laboratory of Bioinformatics and Population Genetics, Seoul National University, Seoul 151-742, Korea, 2Department of Crop Sciences, University of Illinois at Urbana-Champaign, IL 61801, USA and 3Department of Agricultural Biotechnology, Laboratory of Animal Genetic Engineering, Seoul National University, Seoul 151-742, Korea
*To whom correspondence should be addressed. Tel: +82 2 880 4803; Fax: +82 2 883 8812; Email: heebal{at}snu.ac.kr
Received February 10, 2008. Revised June 22, 2008. Accepted July 14, 2008.
In the field of phylogenetics and comparative genomics, it is important to establish orthologous relationships when comparing homologous sequences. Due to the slight sequence dissimilarity between orthologs and paralogs, it is prone to regarding paralogs as orthologs. For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision. Depending on their algorithmic implementations, each of these methods sometimes has increased false negative or false positive rates. Here, we developed a novel algorithm for orthology detection that uses a distance method based on the phylogenetic criterion of minimum evolution. Our algorithm assumes that sets of sequences exhibiting orthologous relationships are evolutionarily less costly than sets that include one or more paralogous relationships. Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree. Unlike tree reconciliation, our algorithm appears free from the problem of incorrect topologies of species and gene trees. The reliability of the algorithm was tested in a comparative analysis with two other orthology detection methods using 95 manually curated KOG datasets and 21 experimentally verified EXProt datasets. Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.